Cougr: Skill for Claude Code

.claude/skills/stellar-competitive-landscape/SKILL.md

stellar-competitive-landscape is a skill for Claude Code from salazarsebas/Cougr. It costs 96 tokens per session (999 once invoked), scanned A, original, MIT.

A research workflow for mapping competing projects in the Stellar ecosystem, which is a network and platform for blockchain applications and digital assets.

In plain words
What is it for?
Use it to identify competitors or related projects for a Stellar idea and group the results by ecosystem category.
Why use it?
It helps turn a project idea into a list of similar Stellar projects by searching curated ecosystem data and a larger repository dataset.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths.

This is salazarsebas/Cougr's own configuration. It tells Claude Code how to work on Cougr itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Cougr configures →

Reuse

Borrowing it

Nothing to install: this file belongs to salazarsebas/Cougr. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/salazarsebas/Cougr/main/.claude/skills/stellar-competitive-landscape/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/salazarsebas/Cougr

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for stellar-competitive-landscape

README.md
[![agentmods](https://agentmods.dev/badge/skills/salazarsebas/cougr/stellar-competitive-landscape/github.svg)](https://agentmods.dev/skills/salazarsebas/cougr/stellar-competitive-landscape)
Your own site
<a href="https://agentmods.dev/skills/salazarsebas/cougr/stellar-competitive-landscape"><img src="https://agentmods.dev/badge/skills/salazarsebas/cougr/stellar-competitive-landscape/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for stellar-competitive-landscape

Your own site · 80×15
<a href="https://agentmods.dev/skills/salazarsebas/cougr/stellar-competitive-landscape"><img src="https://agentmods.dev/badge/skills/salazarsebas/cougr/stellar-competitive-landscape.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 999 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.00999
Opus 5.5 $0.00038 $0.00400
Sonnet 5.5 $0.00019 $0.00200
Haiku 4.5 $0.00010 $0.00100

Measured today against content hash 93670d2072f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

stellar-competitive-landscape scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/stellar-competitive-landscape/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

What this skill does

1. Get the project context

If the user hasn't described their idea, ask: "What are you building, in one sentence?"

Then ask: "Any specific category to compare against? - Financial Protocols, Applications, Developer Tooling, Infrastructure & Services, Payments, Education & Community, or other."

2. Search the ecosystem DB

Read ~/.claude/skills/data/lumenloop/projects.json. If missing, fetch from https://raw.githubusercontent.com/lumenloop/stellar-ecosystem-db/main/ (the YAML files in projects/ - convert on the fly if needed).

Filter by:

  • attributes.category matching the user's stated category (case-insensitive partial match)
  • Description keyword overlap with the user's idea - extract 3-5 keywords from the idea, score each project by how many keywords appear in its description

Return top 10-15 matches ranked by relevance score.

2.5 Mine Electric Capital for what LumenLoop doesn't show

~/.claude/skills/data/electric-capital/stellar-repos.json has ~9000 repos tagged as Stellar - a much wider net than LumenLoop's curated 728. Use it to surface what LumenLoop misses:

  • Emerging players: GitHub orgs with 2+ Stellar repos that aren't in LumenLoop yet (proto-projects, soon-to-launch)
  • Dormant competitors: repos whose names match the user's keywords but show no recent activity (these were attempts that didn't ship - useful signal about why the category might be hard)
  • Cluster detection: if 5+ different orgs are working on the user's exact keyword (e.g., "perps", "vault", "wallet"), the space has more friction than LumenLoop suggests

Filter out noise:

  • Repos with whitebelt, orangebelt, yellowbelt, greenbelt, redbelt in the name (Stellar's tiered training program)
  • Forks of stellar/* official repos with no meaningful divergence
  • Student/tutorial repos (-tutorial, -exercise, -demo suffixes)

The cleaned signal vs LumenLoop catalog gives you the real picture: who's documented, who's stealth-building, who tried and abandoned.

Read the full file on GitHub · 69 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 69 lines · 96 tokens per session scan A 93670d2072f1

Subscribe to this mod's changes

stellar-competitive-landscape is a skill published in the GitHub repository salazarsebas/Cougr (53 stars, last pushed 17d ago), licensed MIT. It adds 96 tokens to every session and 999 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-07.

Related

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stellar-competitive-landscapesalazarsebas/CougrSkill5317d agoMITA96Claude Code
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stellar-forgerylsherdamz-rgb/stellar-forgeSkill175d agoMITA82Claude Code
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